slugColour Image Segmentation Using K-Means, Fuzzy C-Means and Density Based Clustering

Abstract

Image is information which has to be processed effectively. Segmentation, partitions the image into multiple segments. Image segmentation assigns label to every pixel in an image such that pixels with the same label share certain visual characteristic. Clustering is one of the methods used for segmentation. The objective of this paper is to compare the performance of various segmentation techniques for colour images. K-Means, Fuzzy C-Means and Density Based clustering techniques are compared for their performance in segmentation of colour images.

Authors and Affiliations

Preeti, Assistant Professor Kompal Ahuja

Keywords

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  • EP ID EP18351
  • DOI -
  • Views 314
  • Downloads 10

How To Cite

Preeti, Assistant Professor Kompal Ahuja (2014). slugColour Image Segmentation Using K-Means, Fuzzy C-Means and Density Based Clustering. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(6), -. https://europub.co.uk/articles/-A-18351